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相关概念视频

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

267
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
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多功能融合变压器用于模拟带有不平等采样间隔的青素发酵过程.

Yifei Sun1, Xuefeng Yan2, Qingchao Jiang1

  • 1Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, MeiLong Road No. 130, P.O. Box 293, Shanghai, 200237, People's Republic of China.

Bioprocess and biosystems engineering
|October 25, 2023
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概括

一个新的多功能融合变压器 (MFFT) 模型通过整合各种数据来提高生物发酵质量预测. 这种先进的方法可以提高复杂批处理过程的时间序列预测准确度.

关键词:
多个特征的融合融合.青素发酵过程的发酵过程.时间序列预测时间序列预测变压器变压器变压器不平等的抽样时间间隔.

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科学领域:

  • 生物技术是生物技术.
  • 化学工程是化学工程的重要组成部分.
  • 数据科学数据科学数据科学

背景情况:

  • 在生物发酵批量过程中,质量预测至关重要,但由于动态非线性,可变采样和多个数据特征而具有挑战性.
  • 现有的方法难以应对批量处理数据的复杂性,包括不均的持续时间和采样间隔.

研究的目的:

  • 提出一种新的多功能融合变压器 (MFFT) 模型,用于在生物发酵批次过程中准确的时间序列质量预测.
  • 为了应对动态非线性,不平等的抽样和批量过程监测中的多样化数据特征所带来的挑战.

主要方法:

  • 开发了使用序列对序列架构的多功能融合变压器 (MFFT) 模型.
  • 整合了一个变压器并行操作模型来处理可变序列输入和不平等的采样间隔.
  • 通过使用预训练的ResNet50作为菌状况分类器集成图像数据,并开发了一种多功能编码结构.

主要成果:

  • 该MFFT模型在青素发酵的时间序列预测任务中表现出卓越的性能.
  • 拟议的模型有效地融合了图像信息和采样时间数据,以增强特征表示.
  • 在预测批量工艺质量方面,MFFT显著优于现有方法.

结论:

  • 在复杂的生物发酵批处理过程中,MFFT模型为时间序列质量预测提供了强大的解决方案.
  • 整合图像数据和灵活的序列处理机制使MFFT成为工业生物技术的强大工具.
  • 这项研究强调了先进的深度学习架构的潜力,以改善发酵过程的过程监控和控制.